Abstract
Background/Objectives: The severity of radiation-induced toxicity in head and neck cancer (HNC) radiotherapy should be predicted for the prognosis of the patient's quality of life. Multiple organs at risk (OARs) are susceptible to toxicity in the head and neck. Hence, we aimed to investigate the feasibility of evaluating radiation-induced xerostomia and dysphagia based on multi-OAR dosiomics in HNC radiotherapy. Methods: We used radiotherapy treatment planning and toxicity data collected from 44 patients with HNC. High- and low-toxicity grades were classified using dosiomic models derived from multiple OARs. Dosiomic features were computed from the planned dose distribution per OAR. A prediction model was derived using selected dosiomic features and toxicity grades based on extreme gradient boosting for every OAR and all OARs. The model performance was evaluated in terms of the area under the curve (AUC) from leave-one-out cross-validation. Models based on dose volume histogram features and combining these with dosiomic features were derived to compare the prediction performance per OAR. Performance comparisons across OARs were also conducted. Results: The prediction models with the highest AUCs for xerostomia and dysphagia were the dosiomic model using all OARs, with an AUC of 0.843 (95% confidence interval-CI, 0.725-0.961), and that using the middle pharyngeal constrictor muscle, with an AUC of 0.878 (95% CI, 0.772-0.984). Conclusions: The evaluation results demonstrated the feasibility and potential of predicting radiation-induced toxicities based on multi-OAR dosiomics in HNC radiotherapy. Further investigations are required to determine the generalizability of our findings.